乐胖代购免代理版

{"id":"https://openalex.org/W2163344069","doi":"https://doi.org/10.1109/cvprw.2012.6239243","title":"Segmentation and removal of pulmonary arteries, veins and left atrial appendage for visualizing coronary and bypass arteries","display_name":"Segmentation and removal of pulmonary arteries, veins and left atrial appendage for visualizing coronary and bypass arteries","publication_year":2012,"publication_date":"2012-06-01","ids":{"openalex":"https://openalex.org/W2163344069","doi":"https://doi.org/10.1109/cvprw.2012.6239243","mag":"2163344069"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvprw.2012.6239243","pdf_url":null,"source":{"id":"https://openalex.org/S4393918233","display_name":"IEEE Computer Society Conference on Computer Vision and Pattern Recognition workshops","issn_l":"2160-7508","issn":["2160-7508"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056790551","display_name":"Hua Zhong","orcid":"https://orcid.org/0000-0002-5264-6407"},"institutions":[{"id":"https://openalex.org/I4210137693","display_name":"Siemens (United States)","ror":"https://ror.org/04axb7e79","country_code":"US","type":"company","lineage":["https://openalex.org/I1325886976","https://openalex.org/I4210137693"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hua Zhong","raw_affiliation_strings":["Siemens AG Corporate Research, Princeton, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Siemens AG Corporate Research, Princeton, NJ, USA","institution_ids":["https://openalex.org/I4210137693"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051649145","display_name":"Yefeng Zheng","orcid":"https://orcid.org/0000-0003-2195-2847"},"institutions":[{"id":"https://openalex.org/I4210137693","display_name":"Siemens (United States)","ror":"https://ror.org/04axb7e79","country_code":"US","type":"company","lineage":["https://openalex.org/I1325886976","https://openalex.org/I4210137693"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yefeng Zheng","raw_affiliation_strings":["Siemens AG Corporate Research, Princeton, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Siemens AG Corporate Research, Princeton, NJ, USA","institution_ids":["https://openalex.org/I4210137693"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019185222","display_name":"Gareth Funka-Lea","orcid":null},"institutions":[{"id":"https://openalex.org/I4210137693","display_name":"Siemens (United States)","ror":"https://ror.org/04axb7e79","country_code":"US","type":"company","lineage":["https://openalex.org/I1325886976","https://openalex.org/I4210137693"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gareth Funka-Lea","raw_affiliation_strings":["Siemens AG Corporate Research, Princeton, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Siemens AG Corporate Research, Princeton, NJ, USA","institution_ids":["https://openalex.org/I4210137693"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031536207","display_name":"Fernando Vega-Higuera","orcid":null},"institutions":[{"id":"https://openalex.org/I4210153902","display_name":"Siemens Healthcare (Germany)","ror":"https://ror.org/0449c4c15","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210153902"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Fernando Vega-Higuera","raw_affiliation_strings":["Siemens Healthcare, Forchheim, Germany"],"affiliations":[{"raw_affiliation_string":"Siemens Healthcare, Forchheim, Germany","institution_ids":["https://openalex.org/I4210153902"]}]}],"institution_assertions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.395,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":7,"citation_normalized_percentile":{"value":0.578166,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":82,"max":83},"biblio":{"volume":null,"issue":null,"first_page":"24","last_page":"30"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9987,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9987,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9897,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9735,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/coronary-arteries","display_name":"Coronary arteries","score":0.7559661}],"concepts":[{"id":"https://openalex.org/C2778742706","wikidata":"https://www.wikidata.org/wiki/Q18361829","display_name":"Coronary arteries","level":3,"score":0.7559661},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.5661713},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.5002179},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.49688032},{"id":"https://openalex.org/C2776820930","wikidata":"https://www.wikidata.org/wiki/Q9655","display_name":"Artery","level":2,"score":0.48834583},{"id":"https://openalex.org/C2780940725","wikidata":"https://www.wikidata.org/wiki/Q206280","display_name":"Pulmonary artery","level":2,"score":0.48358768},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.47893605},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.47608796},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.45130572},{"id":"https://openalex.org/C2779980429","wikidata":"https://www.wikidata.org/wiki/Q101004","display_name":"Aorta","level":2,"score":0.43824232},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4209894},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.38190055},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3550275},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31802976}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvprw.2012.6239243","pdf_url":null,"source":{"id":"https://openalex.org/S4393918233","display_name":"IEEE Computer Society Conference on Computer Vision and Pattern Recognition workshops","issn_l":"2160-7508","issn":["2160-7508"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.67}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":9,"referenced_works":["https://openalex.org/W1568747707","https://openalex.org/W1767951414","https://openalex.org/W1938796541","https://openalex.org/W2006337443","https://openalex.org/W2038952578","https://openalex.org/W2101689475","https://openalex.org/W2137624270","https://openalex.org/W2148952796","https://openalex.org/W2169146573"],"related_works":["https://openalex.org/W3167885074","https://openalex.org/W3027020613","https://openalex.org/W2892386716","https://openalex.org/W2418603577","https://openalex.org/W2374929157","https://openalex.org/W2374591481","https://openalex.org/W2025191416","https://openalex.org/W2016533837","https://openalex.org/W1998563493","https://openalex.org/W1988449734"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"we":[3],"present":[4],"an":[5],"automatic":[6,119],"heart":[7,26,70,91,113],"segmentation":[8],"system":[9,59,116],"for":[10,72],"helping":[11],"the":[12,15,25,73,94,112],"diagnosis":[13],"of":[14,89,111],"coronary":[16,49],"artery":[17,50],"diseases":[18],"(CAD).":[19],"The":[20,58,75,115],"goal":[21],"is":[22,81,117],"to":[23,67,83,107],"visualize":[24],"from":[27],"a":[28,123],"cardiac":[29,125],"CT":[30,95,126],"image":[31],"with":[32,64],"pulmonary":[33,35],"veins,":[34],"arteries":[36,55],"and":[37,53,120],"left":[38],"atrial":[39],"appendage":[40],"removed":[41],"so":[42],"that":[43],"doctors":[44],"can":[45,121],"clearly":[46],"see":[47],"major":[48],"trees,":[51],"aorta":[52],"bypass":[54],"if":[56],"exist.":[57],"combines":[60],"model-based":[61],"detection":[62],"framwork":[63],"data-driven":[65,103],"post-refinements":[66],"create":[68],"voxel-based":[69],"mask":[71],"visualization.":[74],"marginal":[76],"space":[77],"learning":[78],"[6]":[79],"algorithm":[80],"used":[82],"detect":[84],"mesh":[85],"or":[86],"landmark":[87],"models":[88],"different":[90],"anatomies":[92],"in":[93],"image.":[96],"Guided":[97],"by":[98],"such":[99],"detected":[100],"models,":[101],"local":[102],"refinements":[104],"are":[105],"added":[106],"produce":[108],"precise":[109],"boundaries":[110],"mask.":[114],"fully":[118],"process":[122],"3D":[124],"volume":[127],"within":[128],"5":[129],"seconds.":[130]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2163344069","counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":2},{"year":2014,"cited_by_count":2}],"updated_date":"2025-01-18T15:39:44.500019","created_date":"2016-06-24"}